scholarly journals HIV and Patient Monitoring in Malawi

2018 ◽  
Author(s):  
Brian Williams
Keyword(s):  
Patient Monitoring ◽  
Current System ◽  
Best Interest ◽  
Data Set ◽  
Cd4 Cell Count ◽  
Risk Of Death ◽  
Current State ◽  
Increased Risk ◽  
The World ◽  
World Ranking

Malawi has developed an excellent, nation-wide system for monitoring people infected with HIV and keeping track of key epidemic markers. Their success lies in two things: the focus on simplicity and the use of data collection not only to track the epidemic and identify problems but also to give regular feedback and support to every clinic in the country. This achievement is the more remarkable given that Malawi is one of the poorest countries in the world, ranking 190 out of 194 countries by GDP, but has one of the most severe epidemics of HIV in the world, ranking 9th out of 168 countries by HIV prevalence. We first discuss the current state and likely future epidemic trends in Malawi: unless we know where we are and where we are going we cannot decide what to do or how to do it to in order to achieve a better outcome. We then discuss the history and development of Malawi’s patient monitoring system, as reported in their Integrated HIV Program Reports,ix which have been published quarterly since the beginning of 2004. We consider the current state of patient monitoring and support as reflected in the most recent report for the third quarter (Q3) of 2016 and comment on some of the questions that this raises. Finally, we consider ways in which the current system could be improved by strengthening Malawi’s analytical capacity and making better use of this unique data set. The focus here is on HIV in adultsv because if ART is initiated early in all adults living with HIV this should include testing all pregnant women for HIV and starting them on treatment immediately. However, PMTCT is especially important and care must be given to reducing MTCT and identifying the long-term child survivors of mother-to-child transmission and this demands a complementary assessment. There is an ongoing debate about the relative merits of treatment and prevention in reducing transmission and it should be made clear that the primary reason for starting people on treatment early is that it is in the best interest of the individual patient to start treatment as soon as possible after becoming infected. Allowing a person’s immune system to deteriorate to any degree is not consistent with the clinician’s commitment to ‘first do no harm’ and even those with the highest CD4+ cell count are at a substantially increased risk of death. What matters, therefore, is to get as many people as possible onto ART, ensure that they remain virally suppressed, and consider prevention in this context.

scholarly journals Benchmarking of Machine Learning Models to Assist the Prognosis of Tuberculosis

2021 ◽  
Author(s):  
Maicon Herverton Lino Ferreira da Silva Barros ◽  
Geovanne Oliveira Alves ◽  
Lubnnia Morais Florêncio Souza ◽  
Élisson da Silva Rocha ◽  
João Fausto Lorenzato de Oliveira ◽  
...  
Keyword(s):  
Machine Learning ◽  
Clinical Symptoms ◽  
Treatment Decision ◽  
Gradient Boosting ◽  
Original Form ◽  
Learning Models ◽  
Data Set ◽  
Risk Of Death ◽  
Increased Risk ◽  
Machine Learning Models

Tuberculosis (TB) is an airborne infectious disease caused by organisms in the Mycobacterium tuberculosis (Mtb) complex. In many low and middle-income countries, TB remains a major cause of morbidity and mortality. Once a patient has been diagnosed with TB, it is critical that healthcare workers make the most appropriate treatment decision given the individual conditions of the patient and the likely course of the disease based on medical experience. Depending on the prognosis, delayed or inappropriate treatment can result in unsatisfactory results including the exacerbation of clinical symptoms, poor quality of life, and increased risk of death. This work benchmarks machine learning models to aid TB prognosis using a Brazilian health database of confirmed cases and deaths related to TB in the State of Amazonas. The goal is to predict the probability of death by TB thus aiding the prognosis of TB and associated treatment decision making process. In its original form, the data set comprised 36,228 records and 130 fields but suffered from missing, incomplete, or incorrect data. Following data cleaning and preprocessing, a revised data set was generated comprising 24,015 records and 38 fields, including 22,876 reported cured TB patients and 1,139 deaths by TB. To explore how the data imbalance impacts model performance, two controlled experiments were designed using (1) imbalanced and (2) balanced data sets. The best result is achieved by the Gradient Boosting (GB) model using the balanced data set to predict TB-mortality, and the ensemble model composed by the Random Forest (RF), GB and Multi-layer Perceptron (MLP) models is the best model to predict the cure class.

scholarly journals COVID-19 and the Heart

2020 ◽  
pp. 1-5 ◽  
Author(s):  
Chaitanya Rojulpote ◽  
Karthik Gonuguntla ◽  
Shivaraj Patil ◽  
Abhijit Bhattaru ◽  
Paco Bravo
Keyword(s):  
Cardiovascular System ◽  
The Novel ◽  
Health Crisis ◽  
Risk Of Death ◽  
Increased Risk ◽  
The World ◽  
Significant Burden ◽  
Coronary Syndromes ◽  
Novel Virus ◽  
Underlying Mechanisms

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which causes coronavirus disease 2019 (COVID-19) has resulted in a global health crisis. Prior to the arrival of this viral pandemic, the world was already plagued with a significant burden of cardiovascular disease. With the introduction of the novel virus, the world now faces a double jeapordy. Early reports have suggested an increased risk of death in individuals with underlying cardio-metabolic disorders. The exact effects of COVID-19 on the cardiovascular system are not well determined, however lessons from prior viral epidemics suggest that such infections can trigger acute coronary syndromes, arrhythmias and heart failure via direct and indirect mechanisms. In this article, we aimed to discuss the effects and potential underlying mechanisms of COVID -19 as well as potential implications of treatments targeted against this virus on the cardiovascular system.

scholarly journals Epidemiology and Management of Peritonitis at a Rural Hospital in Zambia

2020 ◽  
Vol 17 (3) ◽  
Author(s):  
Sergiy Karachentsev
Keyword(s):  
Peptic Ulcer ◽  
Acute Appendicitis ◽  
Organ Failure ◽  
Perforated Peptic Ulcer ◽  
Rural Hospital ◽  
Level Of Care ◽  
Significant Morbidity ◽  
Risk Of Death ◽  
Increased Risk ◽  
The World

Background: Peritonitis is a common surgical emergency with varying etiologies encountered the world over. It is associated with significant morbidity and mortality despite intensive research and advances in management. Methods: Records of 119 patients operated on for peritonitis at a rural surgical hospital in Zambia over a 10-year period were retrospectively reviewed. Results: Common sources of peritonitis were perforated peptic ulcer, acute appendicitis, pelvic inflammatory disease, and perforated terminal ileum. Postoperative period became complicated in 42 patients (32.3%). Fourteen patients (11.8%) died postoperatively; the highest level of mortality was in patients with perforated peptic ulcer (26%). Organ failure was found in 29 patients (24.4%) and was associated with increased risk of death. Conclusions: Individual approach with identifying signs of organ failure is essential to determine the patient’s prognosis and decide on the level of care. Patients without organ dysfunction can be successfully managed in a rural surgical hospital. Keywords: Peritonitis, Epidemiology, Morbidity, Mortality, Rural hospital, Zambia

scholarly journals Should I stay or should I go? A retrospective propensity score-matched analysis using administrative data of hospital-at-home for older people in Scotland

BMJ Open ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. e023350 ◽  
Author(s):  
Apostolos Tsiachristas ◽  
Graham Ellis ◽  
Scott Buchanan ◽  
Peter Langhorne ◽  
David J Stott ◽  
...  
Keyword(s):  
Propensity Score ◽  
Administrative Data ◽  
Healthcare Costs ◽  
Data Set ◽  
Risk Of Death ◽  
Level Data ◽  
Increased Risk ◽  
Hospital At Home ◽  
At Home

ObjectivesTo compare the characteristics of populations admitted to hospital-at-home services with the population admitted to hospital and assess the association of these services with healthcare costs and mortality.DesignIn a retrospective observational cohort study of linked patient level data, we used propensity score matching in combination with regression analysis.ParticipantsPatients aged 65 years and older admitted to hospital-at-home or hospital.InterventionsThree geriatrician-led admission avoidance hospital-at-home services in Scotland.Outcome measuresHealthcare costs and mortality.ResultsPatients in hospital-at-home were older and more socioeconomically disadvantaged, had higher rates of previous hospitalisation and there was a greater proportion of women and people with several chronic conditions compared with the population admitted to hospital. The cost of providing hospital-at-home varied between the three sites from £628 to £2928 per admission. Hospital-at-home was associated with 18% lower costs during the follow-up period in site 1 (ratio of means 0.82; 95% CI: 0.76 to 0.89). Limiting the analysis to costs during the 6 months following index discharge, patients in the hospital-at-home cohorts had 27% higher costs (ratio of means 1.27; 95% CI: 1.14 to 1.41) in site 1, 9% (ratio of means 1.09; 95% CI: 0.95 to 1.24) in site 2 and 70% in site 3 (ratio of means 1.70; 95% CI: 1.40 to 2.07) compared with patients in the control cohorts. Admission to hospital-at-home was associated with an increased risk of death during the follow-up period in all three sites (1.09, 95% CI: 1.00 to 1.19 site 1; 1.29, 95% CI: 1.15 to 1.44 site 2; 1.27, 95% CI: 1.06 to 1.54 site 3).ConclusionsOur findings indicate that in these three cohorts, the populations admitted to hospital-at-home and hospital differ. We cannot rule out the risk of residual confounding, as our analysis relied on an administrative data set and we lacked data on disease severity and type of hospitalised care received in the control cohorts.

scholarly journals Benchmarking Machine Learning Models to Assist in the Prognosis of Tuberculosis

Informatics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 27
Author(s):  
Maicon Herverton Lino Ferreira da Silva Barros ◽  
Geovanne Oliveira Alves ◽  
Lubnnia Morais Florêncio Souza ◽  
Elisson da Silva Rocha ◽  
João Fausto Lorenzato de Oliveira ◽  
...  
Keyword(s):  
Machine Learning ◽  
Clinical Symptoms ◽  
Treatment Decision ◽  
Gradient Boosting ◽  
Original Form ◽  
Learning Models ◽  
Data Set ◽  
Risk Of Death ◽  
Increased Risk ◽  
Machine Learning Models

Tuberculosis (TB) is an airborne infectious disease caused by organisms in the Mycobacterium tuberculosis (Mtb) complex. In many low and middle-income countries, TB remains a major cause of morbidity and mortality. Once a patient has been diagnosed with TB, it is critical that healthcare workers make the most appropriate treatment decision given the individual conditions of the patient and the likely course of the disease based on medical experience. Depending on the prognosis, delayed or inappropriate treatment can result in unsatisfactory results including the exacerbation of clinical symptoms, poor quality of life, and increased risk of death. This work benchmarks machine learning models to aid TB prognosis using a Brazilian health database of confirmed cases and deaths related to TB in the State of Amazonas. The goal is to predict the probability of death by TB thus aiding the prognosis of TB and associated treatment decision making process. In its original form, the data set comprised 36,228 records and 130 fields but suffered from missing, incomplete, or incorrect data. Following data cleaning and preprocessing, a revised data set was generated comprising 24,015 records and 38 fields, including 22,876 reported cured TB patients and 1139 deaths by TB. To explore how the data imbalance impacts model performance, two controlled experiments were designed using (1) imbalanced and (2) balanced data sets. The best result is achieved by the Gradient Boosting (GB) model using the balanced data set to predict TB-mortality, and the ensemble model composed by the Random Forest (RF), GB and Multi-Layer Perceptron (MLP) models is the best model to predict the cure class.

scholarly journals Emerging statistics on the Epidemiology of COVID-19: Making prevention in pregnancy less grievous than the disease

2020 ◽  
Vol 3 (1) ◽  
pp. 27-36
Author(s):  
John Imaralu
Keyword(s):  
Pregnant Women ◽  
Emergency Obstetric Care ◽  
Obstetric Care ◽  
Mortality Rates ◽  
Sub Saharan Africa ◽  
Main Body ◽  
Risk Of Death ◽  
Increased Risk ◽  
The World ◽  
Sub Saharan

Background: Pregnant women are a vulnerable group to the COVID-19 infection; although it is expected that adaptive changes of pregnancy put them at increased risk of adverse outcome from any respiratory tract infection, interventions for the COVID-19 may put them in more danger. Nigeria is one of the leading countries with very poor maternal mortality indices and many other sub-Saharan African nations are in the same boat. Contingency plans need to be put in place to prevent precipitous deterioration in mortality rates occasioned by the dreaded SARS- Cov-2 pandemic. This mini-review of literature and WHO global statistics is aimed to determine the trends in COVID-19 transmission and mortality rates to provide evidence-based information that may enable governments to tailor their interventions to the peculiar needs, of sub-Saharan African populations. Main body: Emerging epidemiological trends on transmission and mortality within Africa and the worst affected regions of the world suggests better outcomes of this infection in sub-Saharan Africa, than in other regions of the world. Also, present data allude to similar outcomes between pregnant and non-pregnant women. The present containment measures of isolation and quarantine, including city-wide lockdowns, may put pregnant women at higher risk of death from other causes rather than COVID-19. The danger posed, is the limitation of access to emergency obstetric care services when pregnant women develop non-COVID-19 complications of pregnancy. Conclusion: The COVID-19 pandemic has lower local transmission rates and fatality in Africa, the region where the virus arrived last. While special efforts should be geared at shielding the elderly and infirm from contracting the infection, preventive measures in pregnant women must allow for access to emergency obstetric care to forestall iatrogenic adverse maternal outcomes.

scholarly journals Main Pharmacological Strategies Against SARS-CoV-2

2020 ◽  
Vol 27 (3) ◽  
pp. 153-157
Author(s):  
Thais Gonçalves Fontes ◽  
Afrânio Côgo Destefani
Keyword(s):  
Clinical Trials ◽  
Cardiac Injury ◽  
Structural Heart Disease ◽  
Cardiac Monitoring ◽  
Limited Resources ◽  
Risk Of Death ◽  
Cardiovascular Comorbidities ◽  
Increased Risk ◽  
The World ◽  
Bibliographic Search

There are currently no specifi c drugs for COVID-19. However, several drugs approved for other situations, as well as several investigative agents, are being studied for the treatment of COVID-19 in several hundred clinical trials worldwide. In anticipation of the results of clinical trials, different medical actors around the world have used drugs empirically and with unknown safety profi les. It should be noted that emerging data demonstrated that cardiovascular comorbidities are very common in patients with COVID-19 and that these patients are at increased risk of death. To trace a path of light through the cloudiness that we live on COVID 19, we conducted a bibliographic search, aiming, mostly, to present concise, relevant and scientifi c information. The main groups of drugs and their adverse effects and drug interactions were raised. Specific concerns in patients with COVID-19 include underlying structural heart disease, cardiac injury, kidney and liver dysfunction, limited resources for cardiac monitoring and drug interaction. Clear administration protocols must be in place in all hospitals and clinics that use drugs for the treatment of COVID-19, to assist in research and analysis of possible drugs capable of inhibiting the virus without consequent complications.

Rotational Characteristics of the Green Solar Corona: 1947-1991

1994 ◽  
Vol 144 ◽  
pp. 139-141 ◽  
Author(s):  
J. Rybák ◽  
V. Rušin ◽  
M. Rybanský
Keyword(s):  
Solar Corona ◽  
World Wide ◽  
Rotation Period ◽  
Original Data ◽  
Coronal Emission ◽  
Time Intervals ◽  
Data Set ◽  
The World ◽  
Coronal Emission Line ◽  
Homogeneous Data

AbstractFe XIV 530.3 nm coronal emission line observations have been used for the estimation of the green solar corona rotation. A homogeneous data set, created from measurements of the world-wide coronagraphic network, has been examined with a help of correlation analysis to reveal the averaged synodic rotation period as a function of latitude and time over the epoch from 1947 to 1991.The values of the synodic rotation period obtained for this epoch for the whole range of latitudes and a latitude band ±30° are 27.52±0.12 days and 26.95±0.21 days, resp. A differential rotation of green solar corona, with local period maxima around ±60° and minimum of the rotation period at the equator, was confirmed. No clear cyclic variation of the rotation has been found for examinated epoch but some monotonic trends for some time intervals are presented.A detailed investigation of the original data and their correlation functions has shown that an existence of sufficiently reliable tracers is not evident for the whole set of examinated data. This should be taken into account in future more precise estimations of the green corona rotation period.

DEVELOPMENT OF THE WORLD MARKET OF SERVICES IN TURBULENCE CONDITIONS AND CHANGES

2017 ◽  
Author(s):  
Larysa Nosach ◽  
◽  
Victoria Morgun ◽  
Keyword(s):  
Economic Development ◽  
International Trade ◽  
Service Sector ◽  
World Market ◽  
Global Dimension ◽  
Trade In Services ◽  
Current State ◽  
The World

The author's research of the current state and features of the development of the world market for services in conditions of turbulence of world processes was carried; the world leaders of the service sector in the global dimension and leaders of the most dynamic articles of service categories were identified; the share of world exports of services by countries by the level of their economic development was justified; weaknesses in the assessment of indicators of international trade in services were identified; the research is based on UNCTAD statistics.

Current State and Trends of Export and Import of Fruits and Vegetables in the World

2019 ◽  
pp. 56-63
Author(s):  
Yu.I. Agirbov ◽  
◽  
R.R. Mukhametzyanov ◽  
D.V. Storozhev ◽  
◽  
...  
Keyword(s):  
Fruits And Vegetables ◽  
Current State ◽  
The World
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